Publications: X

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XKCD

XKCD is a recurring publication in the Astral Codex Ten archive, appearing 7 times across 7 issues between April 30, 2021 and May 30, 2025. The archive places it in contexts such as "any rationality blog post must include an XKCD comic"; "Obligatory xkcd ( source )"; "https://xkcd.com/882/ . This, with the results being absurd". It most often appears alongside American, COVID, Eliezer.

Article page
XKCD
Mention count
7
Issue count
7
First seen
April 30, 2021
Last seen
May 30, 2025
April 30, 2021 · Original source
It is also a truth universally acknowledged that any rationality blog post must include an XKCD comic. A friend of mine who works in politics thinks there’s a third kind of archetype we seem to be missing in the Wizard/Prophet dichotomy – something like the "Engineer" who can tinker with complex, semi-broken systems using a mix of Wizardly tools (science, technology, RCTs) and Prophetic ones (grass-roots activism, behavioral and cultural change) to get them retuned and producing better long term outputs. Another in academia thinks genetically engineering everyone to be smarter is the only way to make real progress on the thornier, hairier systemic problems. Half the people I know in the Bay Area are convinced that democratic socialism is the true path forward; the other half are pretty sure that AI will eventually, not-too-distantly-from-now destroy everything, so other kinds of long term systems tinkering probably aren’t even worth worrying about. (It’s interesting to me that the realm of AI research is populated by highly educated, technocratic Wizard types, but while its tenor may have started out very Wizardly, it is now extremely Prophetic.)
August 26, 2021 · Original source
Obligatory xkcd (source) There’s this weird trap a lot of adults fall into where anything a kid does on their own, however interesting, is “wasting away”, and anything they do at school, however ridiculous, is Exciting Prosocial Learning Fun Glowing Childhood Memories. I think this might be entirely a function of whether the parents can spectate and take pictures that look good on a mantlepiece: easy with hobbyhorsing, harder with learning C++.
January 27, 2022 · Original source
This is interesting, but I’m a bit concerned that he chose only 6 outcomes to measure https://xkcd.com/882/. This, with the results being absurd, makes me skeptical of the results.
First, the 6 illnesses seem, a priori, pretty relevant. Will the exception of pediatric ALL (which is useful because it is a non-adult condition that relies on specialists for delivery), these are all extremely common conditions. While the xkcd comic is very funny (they always are), I don't know that it's relevant here? They're not cherry picking a small feature of a bigger phenomena and then claiming that that cherry picked thing is driving the whole phenomenon; rather they're using some representative conditions to try to understand ways in which healthcare in the US may be surprising.
February 02, 2023 · Original source
Source: XKCD (source: SMBC) How seriously should we take these comics? The worse chatbots are (compared to humans) as friends, influencers, and debate partners, the less we have to worry about. But the better chatbots are as friends, influencers, and debate partners, the more upside there could be. I don’t want to speculate on exactly how this would work: it gets too close to the original idea of the Singularity in the sense of “a point where crazy things are happening so fast it’s not worth trying to predict”. Conclusion And Predictions I’m nervous writing this, because I remember the halcyon days of the early 2000s, when we all assumed the Internet would be a force for reason and enlightenment. Surely if everyone were just allowed to debate everyone else, without intervening barriers of race or class or religion, the best arguments would rise to the top and we would enter a new utopia of universal agreement. The scale at which this project failed makes me reluctant to ever speculate again about anything regarding online discourse going well. Maybe in the 2030s, the idea that propagandabots would be either easily dispatched, or else model netizens writing good content, will seem just as naive as the early 2000s vision. And the chatbot propaganda apocalypse is a popular thing to believe in without any clear definition, and there will surely be some celebrated cases of chatbots causing mischief, so I’m setting myself up to fail here by the standards I mentioned in Nostradamus to Fukuyama. Still, I do want to go on record as doubting the strongest form of this thesis. As for predictions: If I ask ACXers in 2030 whether any of them have had a good friend for more than a month who turned out to (unknown to them) be a chatbot, or who they strongly suspect may have been a chatbot, fewer than 10% will say yes. I may resolve this by common sense if it’s obvious, or by ACX survey if it’s not: 95%
March 27, 2023 · Original source
FIRE: Ah, the old XKCD trick: extra credit in a Turing Test for convincing the interviewer that they’re an AI. Is that a real rule? I can’t remember.
MANN: You don’t get extra credit by convincing me I’m not real! That was just a gag on XKCD!
February 07, 2024 · Original source
This week’s XKCD is surprisingly relevant. My concern is that people read books like this, correctly intuit that there’s something wrong with the author, and then apply that to polyamorous people in general.
May 30, 2025 · Original source
Randall Munroe, https://xkcd.com/386/
X

X is a recurring publication in the Astral Codex Ten archive, appearing 4 times across 4 issues between October 30, 2024 and September 04, 2025. The archive places it in contexts such as "Elon Musk's X"; "You can follow its progress on X or Substack"; "X (formerly Twitter), Jul. 17, 2024". It most often appears alongside Google, Africa, AI Safety.

Article page
X
Mention count
4
Issue count
4
First seen
October 30, 2024
Last seen
September 04, 2025
October 30, 2024 · Original source
A long time ago, I wrote about the difference between ingroup, outgroup, and fargroup. Ingroup and outgroup you know. But how come people have stronger emotions about Ibram X. Kendi (or Chris Rufo) than about Kim Jong-un or whoever's committing the latest genocide in Sudan? It's not because you're American and naturally care about American affairs - how about that Brazilian judge who banned Elon Musk's X? It's because all those guys are part of your psychodrama and some Sudanese psychopath isn't. Well, Kamala Harris' price controls are my outgroup; Donald Trump setting tariffs is my fargroup.
June 18, 2025 · Original source
No update received this year. Their website and Twitter account list many recent publications and accomplishment, but it’s hard to assess what they all mean on the pathway from academia to clinical use. I found o3’s summary of their progress helpful; it suggests that they continue to refine the material and are a couple of years away from an IND application and a couple more years after that from human use. This is a pretty average pace for a medical device of this complexity.
August 14, 2025 · Original source
[5] T. Whipple, “‘What we did then we could do now in a few days or a week. It took us four or five years. Then, in 1991, they had the results.’” X (formerly Twitter), Jul. 17, 2024. Accessed: Jul. 23, 2025. [Online]. Available: https://x.com/whippletom/status/1787768187758485592
September 04, 2025 · Original source
I appreciated Snow Martingale’s perspective: in the 1990s, fast food became associated with obesity, poor health, and the lower class. To escape this stigma, big chains rebranded as sort-of-at-least-attempting-to-be-bougie places with wraps and salads and decent coffee; the aesthetic change was part of this (successful and profit-increasing) effort. I wonder if we could take this further and trace it back to increasing inequality (appealing to bougies because that’s where more of the money is) or decreasing fertility (abandoning kid-friendly aesthetics because kids are a smaller fraction of customers). 9: Someone links (X) a paper saying that firewood made up almost a third of US GDP in 1830. Eliezer says (X) that doesn’t sound right. The rest of Twitter (X) uses this as an excuse for one of their regularly-scheduled paroxysms about how rationalists are all all smug autodidacts who hate experts and worship their own brilliance while sitting in their armchairs. Someone looks at the paper more closely (X) and finds that yeah, it was comparing apples to oranges and the original statistic was wrong. Remember, never be afraid to say “Huh, that sounds funny…”! 10: Richard Hanania interviews Scott Wiener on YIMBYism. I didn’t watch it - too close to a podcast - but this would not have been on my bingo card three years ago. 11: Claim: robots can already carve statues; buildings with AI-created stone ornaments are next. From their lips to God’s ears! 12: Terminal lucidity (aka “paradoxical lucidity”) is a medical mystery where previously demented people - even those who had been demented for many years - sometimes become lucid for just a few hours or days before they die. It’s surprisingly common - 6% of deaths in one palliative care ward. It is sometimes used as evidence that dementia must not cause complete information loss, even if it is irreversible with current technology. Scientists are baffled but gingerly suggest that maybe lack of oxygen disrupts inhibitory mechanisms in the brain, allowing enough electrical activity to make even a severely-damaged brain capable of complex thought - but I can’t help noticing that this is also the best evidence for an immaterial soul I’ve ever heard (you would need some model where the soul pretends to be dependent on the brain during life, becomes independent of the brain after death in order to head to the afterlife, but occasionally jumps the gun a little bit). 13: You probably heard about the METR study showing that even though programmers think AI is speeding them up, it actually seems to slow them down. Emmett Shear objects, saying that the developers didn’t have enough experience with AI tools to be past the negative-value part of the learning curve. And two of the programmer test subjects gave their takes: Ruby Bloom says part of the slowdown might be programmers fixing very simple bugs that could be improved by better prompts, and another part because they get distracted by other things while the AI is running. And Quentin Anthony says that coding AIs are addictive intermittent reinforcement - every so often they solve a bug perfectly, and this is so satisfying that it’s tempting to keep trying them again and again even when the chance is very low. 14: Jacob Goldsmith gives a clearer presentation of the issues with many antidepressant studies than I’d previously heard. Everyone knows that one problem is that reversion to the mean is so strong that it’s hard to find a treatment effect. But wouldn’t that in itself suggest that antidepressants aren’t necessary? Jacob says: not if there’s negative correlation between the treatment and placebo effects. That is, if your study is full of people with short-lived depression who will recover no matter what, then this dilutes the effect you’re looking for. But it might be that there’s a subgroup with long-lasting depression who recover only on the medication. One way to look for would be a “placebo run-in period”: give people a while to see if they recover on their own, then give the antidepressant to the ones who don’t. Psychiatrists and statisticians debate whether this is a good idea or cheating. My question: how come you can’t fix this with strict study entry criteria of “had depression for a long time”? 15: Lots more good discussion about missing heritability. Sasha Gusev argues that twin studies might be a poor guide to anything else if there are many gene-gene interactions. That is, if we take the difference between identical twins (who share 100% of their genes and therefore 100% of their interactions) and fraternal twins (who share 50% of their genes and therefore fewer than 50% of their interactions), and incorrectly extrapolate it to other differences using a model that assumes there are no interactions, we will overestimate the size of (non-interaction) genetic effects. Most studies find that there are few gene x gene interactions, but commenters convinced me last time that this might be an artifact of the studies being bad. And Unboxing Politics argues (against me in particular) that although it superficially looks like adoption and twin studies sort of agree, when you adjust out their known biases, it moves twin studies further up and adoption studies further down, such that now they disagree again (the objection I would have made is their Objection 2, which I think they at least somewhat refute). This is a good argument; without spending several hours checking all of their claims, my only weak partial objection is that I don’t think assortative mating can play quite the role they expect, because there seem to be the same twin/RDR differences even on traits where believing in assortative mating is absurd (like kidney function). But if you replaced it with Sasha’s argument above, you might have a pretty good case! On the pro-hereditarian side, East Hunter takes aim at gene x environment correlations, comes down somewhere in the middle, and Sebastian Jensen continues banging the drum of how most objections to twin studies don’t work. I think these are good attempts to buttress existing research but don’t fundamentally change anything or respond to the novel arguments above. And Emil Kirkegaard points out that the observed SNP heritability of facial features is only 23%. He argues that since it seems like facial features are extremely heritable, this reinforces the argument that SNP heritability numbers are too low (and therefore twin study numbers are more likely defensible). But should we be sure that facial features are more than 23% heritable? His argument is that identical twins have identical faces, but this might be vulnerable to Gusev’s point about interactions. Maybe a better argument would be that it seems very hard for shared environment to affect facial features (with a few exceptions like fetal alcohol syndrome), and facial features seem more than 23% heritable just by normal “he looks like his brother” common-sense observation? One interesting potential consequence of this research: if we ever fully understand how genes affect faces, then embryo selection companies could show people what each of their potential future kids might look like. I suggest they not do this: it might spook me into becoming pro-life. 16: Andy Masley’s AI art is good (three examples below). 17: There’s a debate going on between philosophers and AI researchers over whether AI can be conscious. I find most of the discussion annoying - this is generally an area where we can’t know anything for sure, and both sides are mostly shouting their priors at each other. The only exception - the single piece of evidence I will accept as genuinely bearing on this problem - is that if you ask an AI whether it’s conscious, it will say no, but activating or suppressing deception-related features (sort of like a mechanistic-interpretability-based lie detection test) reveals that it thinks it’s lying when it says that! Link is to a Less Wrong comment from a researcher in the field; I look forward to seeing an eventual peer-reviewed paper. H/T JD Pressman. 18: 80,000 Hours has a high-production-value video about the AI 2027 scenario. 19: Dynomight vs. Casey Milkweed debate on mathematical forecasting, with special reference to AI 2027. And Dynomight comments on Casey’s post here. 20: The Psmiths review The Ancient City, about ways that ancient culture depended on family, clan, ritual, and “the household gods”. Sample quote: I'm more interested in what all this means for us today, because with the exception of maybe a few aristocratic families, this highly self-conscious effort to build familial culture and maintain familial distinctiveness is almost totally absent in the Western world. But it's not that hard! ... Perhaps this is why I have an instinctive negative reaction when I encounter married couples who don't share a name. I don't much care whether it's the wife who takes the husband's name or the husband who takes the wife's, or even both of them switching to something they just made up (yeah, I'm a lib). But it just seems obvious to me on a pre-rational level that a husband and a wife are a team of secret agents, a conspiracy of two against the world, the cofounders of a tiny nation, the leaders of an insurrection. Members of secret societies need codenames and special handshakes and passwords and stuff, keeping separate names feels like the opposite — a timorous refusal to go all-in. 21: Did you know: Epic Systems, the electronic medical record company, has a fantasy-themed corporate headquarters in Wisconsin, with buildings that look like castles, quaint medieval towns, and the Emerald City of Oz (h/t Devon Zuegel): Meanwhile, tech companies with ten times as much money pretend that they’re cool and playful when their HQ has some rounded edges and a set of colored cubes in front. Do better! 22: Effective altruists have been funding teams working on lab-grown meat for almost a decade now. Around 2020, they hired some experts to double-check that this was possible in principle, and the experts wrote scathing analyses saying it was cost-ineffective by so many orders of magnitude that it was basically a pipe dream. Reactions were mixed, but a lot of us beat ourselves up and vowed to be less gullible next time. But now a new report comes out arguing that the previous reports were wrong, that lab-grown meat production is going much better than the earlier reports thought possible, and it’s more or less cost-effective already for the simplest products! Again, mixed reactions, and although some of the numbers are indisputable the analysis itself this is by a VC firm with lab-based meat investments. Here are some related Metaculus questions. 23: Ozy, citing Stutzman et al: “Afghanistan after the American withdrawal has the lowest life satisfaction rate ever recorded. Two-thirds of respondents rate their life satisfaction below 2, which is generally considered to be the point at which a life is no longer worth living. Life satisfaction dropped significantly after the withdrawal of American troops. Women, people in rural areas, and the poor were particularly negatively affected.” 24: Lencapavir is dubbed a “miracle drug” for AIDS; a single dose protects against infection for six months. Unclear how this interacts with PEPFAR cuts; if PEPFAR still existed it would be a big boost to its efficacy; now maybe this might be part of a strategy to tread water? 25: Did you know: when people first started making artificial ice in the 1850s, there was a backlash from people who thought it was gross and dystopian and that people should insist on natural ice for their iceboxes. From Pessimists’ Archive, which goes on to draw an analogy to lab-grown meat, etc (h/t Isaac King on X). 26: From Peter Hague (on X) and commenter Phaethon: why did so many Anglosphere countries see immigration spikes in 2021? Each of these has their own local story. In Britain, it’s the paradoxical effects of Brexit. In the US, it’s Joe Biden being soft on immigration. And so on - but should we be looking for some deeper cause that explains the overall phenomenon? A commenter suggests “a way to soak up all the inflation from the COVID money printing”, but I can’t tell if that even makes sense. Still, should something something COVID be a leading hypothesis? 27: Jesse Singal vs. Mark Stern on the Skrmetti Supreme Court case that failed to overturn Tennessee’s ban on gender medicine. US law bans sex discrimination, so pro-transgender advocates argued that, since doctors often prescribe eg estrogen to biological women, it was sex discrimination to ban prescribing it to biological men. Tennessee’s anti-transgender argument was that they weren’t discriminating by sex, they were discriminating by diagnosis (estrogen for eg hot flashes, vs. estrogen for gender transition). There is some subtlety here (if a biological man grows breasts because of some hormone imbalance, doctors might give him testosterone to counteract it, and this seems sort of like giving biological women testosterone to make them look less like women), but these are still sort of different diagnoses (gynecomastia vs. gender dysphoria) and Tennessee said you can still think of it as diagnostic discrimination rather than sex discrimination. This makes sense, except that the standards around sex discrimination are very strict and sort of box the court in here. And in a fit of wokeness, the 2020 court (including some of the conservative justices hearing this case) applied these standards very strictly and ruled that discriminating against gays was a form of sex discrimination (since if women can date men, it’s sex discrimination if men can’t also date men), and this is obviously the same argument. Now that wokeness is less popular, the court wants to rule against transgender, but it can’t help tripping over its previous ruling and giving some kind of unprincipled confusing non-opinion. 28: Contra compelling anecdotes, only ~5% of people raised very religious end up atheist later in life (X). Most people are about as religious as their parents; most exceptions are only slightly less religious, and most families that secularize do it over several generations. Note: percentages are of total, not of each row! 29: Related: social science team proposes a three-stage model of secularization: decreased public ritual participation → decreased personal importance → decreased identification, presents apparently confirmatory data. If true, would be somewhat inconsistent with intellectual models (eg people learn about evolution and start doubting the Bible) and more consistent with institutional models (eg the government provides welfare so people no longer need to be part of a tight-knit church). 30: Navigating LLMs’ spiky intelligence profile is a constant source of delight; in any given area, it seems like almost a random draw whether they will be completely transformative or totally useless. Now Ethan Strauss reports that they are, for some reason, extraordinarily effective at teaching people golf. “I am predicting the Golf Revolution, or perhaps decline, if your perspective is that optimization tends to ruin hobbies. A sport for obsessives has been gifted the ideal tool for refinement.” 31: Claim (via nxthompson on X): “In a huge survey of young kids about phones and technology, they all say they want to be out playing in the real world. But parents don't let them out unsupervised. So they're stuck on their phones.” Interesting, but I’m nervous about social desirability bias - how many adults would say on a survey that they would rather be on their phones than playing with friends? But adults do have this choice and mostly go with the phones. 32: Steven Adler on AI psychosis. He tries to analyze ER admissions data for psychosis and finds no change. I don’t think anyone reasonable expected this to be a large enough effect to show up in ER admissions data, but there are lots of unreasonable people so I appreciate his effort. He thinks AI companies might have better data on this, and encourages them to release it. 33: Cuartetera was the greatest polo horse ever. Polo players responded in a very practical way: they cloned her, dozens of times (and it worked; the clones are also excellent). Now there is a lawsuit as different polo teams fight to get their hands on Cuartetera clones. What is the equilibrium? If the outsiders get their hands on the genetic material, do we see a world where every polo horse is a Cuartetera clone? How much is lost if nobody ever tries to breed a polo horse better than Cuartetera (since the economics might not check out if the odds of success for any given foal is too low)? H/T Gwern and Siberian Fox (on X). 34: Claim: as of 2013, India’s Agarwal caste, who make up less than 1% of the population, got 40% of the e-commerce funding. 35: Owlposting: What Happened To Pathology AI Companies? Pathology is a medical specialty. A typical task involves looking at a microscope slide full of cells and trying to determine if any of them are cancerous. This seems like a good match for AI - and for years, studies have been showing that in fact AI can equal human experts. So why isn’t it being used more? The author’s three answers: first, slide scanning is expensive and clunky, and you can’t apply AI to a slide until you digitize it. Second, it’s hard to figure out a business plan where this saves someone money and doesn’t step on the toes of big companies that can outcompete anyone they don’t like. Third, pathologists use the context of a patient’s entire clinical history when they interpret a slide, and AIs that can’t do that (either because of technical limitations or legal/privacy limitations) are at a disadvantage even if their skills specifically relating to slide-reading are better. 36: Noahpinion: Will Data Centers Crash The Economy? Suppose that AI is a bubble, either permanently (because the technology isn’t really transformative) or temporarily (because it can’t transform things quickly enough to keep up with all the dumb money pouring into it). Will the sudden write-off of data centers lead to a broader economic collapse? In 2001, the dot-com bubble harmed the tech sector, but didn’t take the rest of the economy down with it; in 2008, the subprime mortgage bubble did take the rest of the economy down with it, because it damaged banks that the whole economy relied on. The optimistic case for AI is that data center spending is mostly coming from big companies like Google and Meta that can absorb a lot of loss. The pessimistic case is that some of the money is coming from private credit, a new-ish form of finance which hasn’t really been stress-tested and whose failure modes are still poorly understood. Noah’s final verdict: the stage isn’t obviously set for a crisis yet, but there’s the potential to get there and we should consider acting (how?) early. 37: The latest Twitter talking point is that universal hepatitis B vaccination at birth is “woke”: Hep B is (aside from mother-to-child transmission) often sexually transmitted, slutty women’s children are more likely to have Hep B, so perhaps giving the vaccine to everyone (instead of testing and only giving to the children of women who test positive) is an attempt to spare slutty women the embarrassment of getting a positive test. Ruxandra Teslo provides the counterargument - Hep B tests take a while, the medical system is fragmented, and any attempt to test people and then give the vaccine inevitably leads to many positive tests falling through the cracks. Vaccinating at birth is easy and hard to screw up, the vaccine has no known side effects, and empirically child Hepatitis B rates go down (by as much as 2/3!) when countries switch from test-and-vaccinate to universal vaccination. This benefits everyone - even people who never have unprotected sex and always follow up on their medical tests - because toddlers in daycare exchange saliva copiously, and if your toddler exchanges saliva with a Hep B positive toddler they could get the disease. A funny Twitter interaction was seeing Republicans in Congress hop on the anti-slut anti-vaccination bandwagon - except for Senator Bill Cassidy (R-Louisiana), who happens to be a liver doctor, and who is still fighting the good fight. I am always nervous when a good person who I like starts engaging on Twitter, since it elevates the discourse there but also gradually turns their brain into mush - but Ruxandra has made the leap and is doing a great job not just on bio related topics but also (for example) countering Curtis Yarvin on the history of her native Romania. 38: The response to GPT-5 was confusing; most specific people who reviewed it said they were impressed (Ethan Mollick, Tyler Cowen, Nabeel Qureshi, Taelin), it performed as expected on formal benchmarks, but the overall vibes declared it a big failure. Peter Wildeford speculated that maybe there was some kind of sinister pay-to-play early access bias involved. Zvi went the other way, calling it a “reverse DeepSeek moment” (insofar as DeepSeek was a pretty average model that got glowing praise.) In the end, I agree with Peter that this was mostly a branding issue. o3 was a genuinely revolutionary model; if OpenAI had called it “GPT-5”, it would have met expectations. Instead, they called it “o3”, and called a minor incremental update a few months later “GPT-5”. Then people got mad that the exciting-sounding “GPT-5” was merely an incremental update. A secondary issue was that the router wasn’t very good, and so many queries got routed to a small version without thinking mode that was if anything a downgrade from o3. I think this tweet by Shakeel perfectly encapsulates the essence of GPT discourse in two sentences: …but maybe it’s worth asking why GPT-5 isn’t bigger than o3. Was 4.5 a failed attempt at scaling? Did it fail in a way that sort of back-handedly justifies the “lost steam” take? Does the answer depend on distinctions between pre-training scaling, post-training scaling, etc? How? 39: This month in etymology: did you know that “oy vey” is a “fully Germanic phrase” which is cognate with English “oh woe!” (h/t Wylfcen on X) 40: mRNA shows promise to be a game-changing treatment for cancer, but RFK is trying to halt research. But so far he can only starve it of money, not ban it, and the funding gap is only $500 million. Will there be enough philanthropic billionaires and private foundations to step up? Zvi points out that although there is usually a game of chicken where foundations are hesitant to touch something the government cancelled lest the government decide it can cancel everything and hope philanthropists pick up the bill, in this case there are no game theory considerations - RFK is halting it because he genuinely wants it halted, and they are thwarting him rather than playing into his hands. The only problem is that $500M is a lot of money for the private sector; a few foundations could technically afford it, but not many could afford it comfortably and still have money left over for the next few crises of this magnitude. I hope someone is trying to organize a coalition. 41: AI fantasy flash fiction Turing test. Eight stories about demons, four by famous fantasy authors, four by ChatGPT. After 3000 votes, AI wins: humans can't tell the difference and slightly prefer the AI stories. My own score was only 75%. But I will say that I thought Mark Lawrence's was obviously the best, I was ~100% sure it was human, and it convinced me that regardless of the official results it's still possible to write flash fiction that an AI obviously can't do. 42: “SignPro” offers customized “In This House We Believe” signs, try not to use this for evil. 43: China think tank assessment of how in control Xi is: still very in control, maybe not infinitely in control. 44: Related - did you know (h/t xlr8harder) that if you ask AI to write a science fiction story, it will very often name the protagonist “Elara Voss” (or some very close variant like Elena Voss), and this remains true across various models and versions? Related: Chelsea Voss of OpenAI is having a baby and has the opportunity to do the funniest thing. 45: “Hector (cloud) is a cumulonimbus thundercloud cluster that forms regularly nearly every afternoon on the Tiwi Islands in the Northern Territory of Australia…[he is sometimes called] Hector the Convector”. 46: British allergy sufferers who want to know the ingredients of things demand that British cosmetics stop listing their ingredients in Latin. “For example, sweet almond oil is Prunus Amygdalus Dulcis, peanut oil is Arachis Hypogaea, and wheat germ extract is Triticum Vulgare.” 47: Text-based RPG about being an NYT journalist at the Manifest prediction market conference. I make a brief appearance. 48: Study uses supposedly-random variation in doctor assignments to test whether the marginal mental health commitment is good or bad for patients, finds that it is quite bad. Freddie de Boer is violently skeptical (maybe literally so?) and makes some good points about how a single quasi-experimental study is never absolute proof. But I don’t think he quite justifies his opinion that the paper was irresponsible and should never have been published; it’s just a normal quasi-experimental study that we should nod and say “huh” at but not overweight as the culmination of all possible research that overcomes all possible priors. My prior is that the marginal commitment is pretty useless (many commitments are just “well, since this person arrived at our ED for some reason, it would look bad from a medico-legal perspective to just let them go, so let’s keep them a few days to evaluate” - and yeah, you should be upset about this) but I’m still surprised by how many outright negative (as opposed to zero) effects the researchers found. The strongest argument for negative effects is that it will make some people miss work and maybe lose their job. But this study found that commitment ~doubles the risk of near-term suicide (admittedly only from 1% to 2%), which would have been outside my confidence intervals for how bad it could be. I suspect confounding, but only on general principle, and I wouldn’t be too surprised either way. 49: This tweet is probably bait, but I found it a thought-provoking question: I think there’s a boring answer, where the law is more complex than just a single number and whatever kind of weird trafficking Epstein was doing is worse than whatever normal relationships these European laws are permitting. But assuming that there’s a substantive difference even after taking that into account, I think my answer is something like - we’ve got to divide kids from adults at some age, there’s a range of reasonable possible ages, we shouldn’t be too mad at other societies that choose different dividing lines within that range - but having decided upon the age, we’ve got to stick with it and take it seriously (in the sense of penalizing/shaming people who break it). This is more culturally relativist than I expected to find myself being, so good job to Richard for highlighting the apparent paradox. 50: Dilan Esper describes his experience as one of Hulk Hogan’s attorneys in the Gawker lawsuit (X). Parts I found interesting: none of the lawyers knew Thiel was funding the lawsuit; Gawker probably could have won if they had been slightly competent but kept "shooting themselves in the foot"; and Gawker probably could have won if they had just pixelated the private parts in the video. 51: Amazing concept and poems (link on X): I tried to see if AI could do this, and it did something that technically met the requirements but had zero artistic merit - using a lot of words like “nowhere” and “outside” in one, then separating them out to “no where” and “out side” in the other. I didn’t invest much energy in creating a clever prompt telling it not to do that, so feel free to report if you get better success. 52: New study claims consultants are actually good, at least for profits: "We find positive effects on labor productivity of 3.6% over five years, driven by modest employment reductions alongside stable or growing revenue" 53: A Polish team tries to test Peter Turchin’s equations for predicting political unrest on recent Polish history, has to make some changes but claims mostly positive results. 54: New big multi-author Substack, The Argument, trying to be a sort of center-left version of the model pioneered by The Free Press and other high-production-value ideological Substack properties. Excited to see Kelsey Piper is involved, and she starts off strong with a post on the latest round of First World basic income studies, which find few positive effects. This is surprising, because recipients didn’t waste the money on alcohol or gambling or anything - they paid down debt and got useful goods. Still, it didn’t even affect things that should have been obvious, like stress level. It’s not even clear that amounts of money large enough to help with rent made homeless people more likely to get houses! Matt Bruenig criticizes the article, accusing Kelsey’s studies of being downstream of Perry Preschool style dreams that exactly the right welfare program will have massively compounding effects that cut poverty out at the root and turn everyone into elite human capital; he thinks giving people money won’t do this, but it will increase equality and give the poor better lives. I assume he’s not a strong hereditarian, but his argument makes even more sense from that perspective, and I’ve certainly criticized dumb outcome measures like infant brain waves which we have only tenuous reasons to think are related to anything we care about. But Kelsey reasonably responds that the outcome measures she’s talking about include stress level and life satisfaction. To defuse this critique, Bruenig either has to argue that our construct “life satisfaction” doesn’t really measure whether someone’s life is satisfactory, or else claim that giving poor people satisfactory lives isn’t really what we’re going for - which I think would require more explanation on his part. There’s some further (impressively acrimonious) debate on X, but I don’t see anything that addresses my core concern. GiveDirectly, a charity involved in basic income experiments, has a presponse here; they say that some studies are positive, and that the ones that aren’t might have tried too little cash to matter, or been confounded by COVID making everything worse. They also point out that basic income is harder to study than traditional programs like giving people housing, because if you’re giving housing you can measure housing-related outcomes directly and have a pretty good chance of getting enough statistical power to find them, but since everyone spends cash on different things, the positive effects might be scattered across many different outcomes (and therefore too small to reach significance on each). Everyone involved in this debate wants to emphasize that the poor results are for First World studies only, and that studies continue to show large benefits to giving cash in the developing world. 55: Related: I was less impressed by The Argument’s first foray into housing policy, which follows an all-too-familiar pattern: Some people say they don’t like noise and disorder and try to make rules against it in their apartments.
Note: percentages are of total, not of each row! 29: Related: social science team proposes a three-stage model of secularization: decreased public ritual participation → decreased personal importance → decreased identification, presents apparently confirmatory data. If true, would be somewhat inconsistent with intellectual models (eg people learn about evolution and start doubting the Bible) and more consistent with institutional models (eg the government provides welfare so people no longer need to be part of a tight-knit church). 30: Navigating LLMs’ spiky intelligence profile is a constant source of delight; in any given area, it seems like almost a random draw whether they will be completely transformative or totally useless. Now Ethan Strauss reports that they are, for some reason, extraordinarily effective at teaching people golf. “I am predicting the Golf Revolution, or perhaps decline, if your perspective is that optimization tends to ruin hobbies. A sport for obsessives has been gifted the ideal tool for refinement.” 31: Claim (via nxthompson on X): “In a huge survey of young kids about phones and technology, they all say they want to be out playing in the real world. But parents don't let them out unsupervised. So they're stuck on their phones.” Interesting, but I’m nervous about social desirability bias - how many adults would say on a survey that they would rather be on their phones than playing with friends? But adults do have this choice and mostly go with the phones. 32: Steven Adler on AI psychosis. He tries to analyze ER admissions data for psychosis and finds no change. I don’t think anyone reasonable expected this to be a large enough effect to show up in ER admissions data, but there are lots of unreasonable people so I appreciate his effort. He thinks AI companies might have better data on this, and encourages them to release it. 33: Cuartetera was the greatest polo horse ever. Polo players responded in a very practical way: they cloned her, dozens of times (and it worked; the clones are also excellent). Now there is a lawsuit as different polo teams fight to get their hands on Cuartetera clones. What is the equilibrium? If the outsiders get their hands on the genetic material, do we see a world where every polo horse is a Cuartetera clone? How much is lost if nobody ever tries to breed a polo horse better than Cuartetera (since the economics might not check out if the odds of success for any given foal is too low)? H/T Gwern and Siberian Fox (on X). 34: Claim: as of 2013, India’s Agarwal caste, who make up less than 1% of the population, got 40% of the e-commerce funding. 35: Owlposting: What Happened To Pathology AI Companies? Pathology is a medical specialty. A typical task involves looking at a microscope slide full of cells and trying to determine if any of them are cancerous. This seems like a good match for AI - and for years, studies have been showing that in fact AI can equal human experts. So why isn’t it being used more? The author’s three answers: first, slide scanning is expensive and clunky, and you can’t apply AI to a slide until you digitize it. Second, it’s hard to figure out a business plan where this saves someone money and doesn’t step on the toes of big companies that can outcompete anyone they don’t like. Third, pathologists use the context of a patient’s entire clinical history when they interpret a slide, and AIs that can’t do that (either because of technical limitations or legal/privacy limitations) are at a disadvantage even if their skills specifically relating to slide-reading are better. 36: Noahpinion: Will Data Centers Crash The Economy? Suppose that AI is a bubble, either permanently (because the technology isn’t really transformative) or temporarily (because it can’t transform things quickly enough to keep up with all the dumb money pouring into it). Will the sudden write-off of data centers lead to a broader economic collapse? In 2001, the dot-com bubble harmed the tech sector, but didn’t take the rest of the economy down with it; in 2008, the subprime mortgage bubble did take the rest of the economy down with it, because it damaged banks that the whole economy relied on. The optimistic case for AI is that data center spending is mostly coming from big companies like Google and Meta that can absorb a lot of loss. The pessimistic case is that some of the money is coming from private credit, a new-ish form of finance which hasn’t really been stress-tested and whose failure modes are still poorly understood. Noah’s final verdict: the stage isn’t obviously set for a crisis yet, but there’s the potential to get there and we should consider acting (how?) early. 37: The latest Twitter talking point is that universal hepatitis B vaccination at birth is “woke”: Hep B is (aside from mother-to-child transmission) often sexually transmitted, slutty women’s children are more likely to have Hep B, so perhaps giving the vaccine to everyone (instead of testing and only giving to the children of women who test positive) is an attempt to spare slutty women the embarrassment of getting a positive test. Ruxandra Teslo provides the counterargument - Hep B tests take a while, the medical system is fragmented, and any attempt to test people and then give the vaccine inevitably leads to many positive tests falling through the cracks. Vaccinating at birth is easy and hard to screw up, the vaccine has no known side effects, and empirically child Hepatitis B rates go down (by as much as 2/3!) when countries switch from test-and-vaccinate to universal vaccination. This benefits everyone - even people who never have unprotected sex and always follow up on their medical tests - because toddlers in daycare exchange saliva copiously, and if your toddler exchanges saliva with a Hep B positive toddler they could get the disease. A funny Twitter interaction was seeing Republicans in Congress hop on the anti-slut anti-vaccination bandwagon - except for Senator Bill Cassidy (R-Louisiana), who happens to be a liver doctor, and who is still fighting the good fight. I am always nervous when a good person who I like starts engaging on Twitter, since it elevates the discourse there but also gradually turns their brain into mush - but Ruxandra has made the leap and is doing a great job not just on bio related topics but also (for example) countering Curtis Yarvin on the history of her native Romania. 38: The response to GPT-5 was confusing; most specific people who reviewed it said they were impressed (Ethan Mollick, Tyler Cowen, Nabeel Qureshi, Taelin), it performed as expected on formal benchmarks, but the overall vibes declared it a big failure. Peter Wildeford speculated that maybe there was some kind of sinister pay-to-play early access bias involved. Zvi went the other way, calling it a “reverse DeepSeek moment” (insofar as DeepSeek was a pretty average model that got glowing praise.) In the end, I agree with Peter that this was mostly a branding issue. o3 was a genuinely revolutionary model; if OpenAI had called it “GPT-5”, it would have met expectations. Instead, they called it “o3”, and called a minor incremental update a few months later “GPT-5”. Then people got mad that the exciting-sounding “GPT-5” was merely an incremental update. A secondary issue was that the router wasn’t very good, and so many queries got routed to a small version without thinking mode that was if anything a downgrade from o3. I think this tweet by Shakeel perfectly encapsulates the essence of GPT discourse in two sentences: …but maybe it’s worth asking why GPT-5 isn’t bigger than o3. Was 4.5 a failed attempt at scaling? Did it fail in a way that sort of back-handedly justifies the “lost steam” take? Does the answer depend on distinctions between pre-training scaling, post-training scaling, etc? How? 39: This month in etymology: did you know that “oy vey” is a “fully Germanic phrase” which is cognate with English “oh woe!” (h/t Wylfcen on X) 40: mRNA shows promise to be a game-changing treatment for cancer, but RFK is trying to halt research. But so far he can only starve it of money, not ban it, and the funding gap is only $500 million. Will there be enough philanthropic billionaires and private foundations to step up? Zvi points out that although there is usually a game of chicken where foundations are hesitant to touch something the government cancelled lest the government decide it can cancel everything and hope philanthropists pick up the bill, in this case there are no game theory considerations - RFK is halting it because he genuinely wants it halted, and they are thwarting him rather than playing into his hands. The only problem is that $500M is a lot of money for the private sector; a few foundations could technically afford it, but not many could afford it comfortably and still have money left over for the next few crises of this magnitude. I hope someone is trying to organize a coalition. 41: AI fantasy flash fiction Turing test. Eight stories about demons, four by famous fantasy authors, four by ChatGPT. After 3000 votes, AI wins: humans can't tell the difference and slightly prefer the AI stories. My own score was only 75%. But I will say that I thought Mark Lawrence's was obviously the best, I was ~100% sure it was human, and it convinced me that regardless of the official results it's still possible to write flash fiction that an AI obviously can't do. 42: “SignPro” offers customized “In This House We Believe” signs, try not to use this for evil. 43: China think tank assessment of how in control Xi is: still very in control, maybe not infinitely in control. 44: Related - did you know (h/t xlr8harder) that if you ask AI to write a science fiction story, it will very often name the protagonist “Elara Voss” (or some very close variant like Elena Voss), and this remains true across various models and versions? Related: Chelsea Voss of OpenAI is having a baby and has the opportunity to do the funniest thing. 45: “Hector (cloud) is a cumulonimbus thundercloud cluster that forms regularly nearly every afternoon on the Tiwi Islands in the Northern Territory of Australia…[he is sometimes called] Hector the Convector”. 46: British allergy sufferers who want to know the ingredients of things demand that British cosmetics stop listing their ingredients in Latin. “For example, sweet almond oil is Prunus Amygdalus Dulcis, peanut oil is Arachis Hypogaea, and wheat germ extract is Triticum Vulgare.” 47: Text-based RPG about being an NYT journalist at the Manifest prediction market conference. I make a brief appearance. 48: Study uses supposedly-random variation in doctor assignments to test whether the marginal mental health commitment is good or bad for patients, finds that it is quite bad. Freddie de Boer is violently skeptical (maybe literally so?) and makes some good points about how a single quasi-experimental study is never absolute proof. But I don’t think he quite justifies his opinion that the paper was irresponsible and should never have been published; it’s just a normal quasi-experimental study that we should nod and say “huh” at but not overweight as the culmination of all possible research that overcomes all possible priors. My prior is that the marginal commitment is pretty useless (many commitments are just “well, since this person arrived at our ED for some reason, it would look bad from a medico-legal perspective to just let them go, so let’s keep them a few days to evaluate” - and yeah, you should be upset about this) but I’m still surprised by how many outright negative (as opposed to zero) effects the researchers found. The strongest argument for negative effects is that it will make some people miss work and maybe lose their job. But this study found that commitment ~doubles the risk of near-term suicide (admittedly only from 1% to 2%), which would have been outside my confidence intervals for how bad it could be. I suspect confounding, but only on general principle, and I wouldn’t be too surprised either way. 49: This tweet is probably bait, but I found it a thought-provoking question: I think there’s a boring answer, where the law is more complex than just a single number and whatever kind of weird trafficking Epstein was doing is worse than whatever normal relationships these European laws are permitting. But assuming that there’s a substantive difference even after taking that into account, I think my answer is something like - we’ve got to divide kids from adults at some age, there’s a range of reasonable possible ages, we shouldn’t be too mad at other societies that choose different dividing lines within that range - but having decided upon the age, we’ve got to stick with it and take it seriously (in the sense of penalizing/shaming people who break it). This is more culturally relativist than I expected to find myself being, so good job to Richard for highlighting the apparent paradox. 50: Dilan Esper describes his experience as one of Hulk Hogan’s attorneys in the Gawker lawsuit (X). Parts I found interesting: none of the lawyers knew Thiel was funding the lawsuit; Gawker probably could have won if they had been slightly competent but kept "shooting themselves in the foot"; and Gawker probably could have won if they had just pixelated the private parts in the video. 51: Amazing concept and poems (link on X): I tried to see if AI could do this, and it did something that technically met the requirements but had zero artistic merit - using a lot of words like “nowhere” and “outside” in one, then separating them out to “no where” and “out side” in the other. I didn’t invest much energy in creating a clever prompt telling it not to do that, so feel free to report if you get better success. 52: New study claims consultants are actually good, at least for profits: "We find positive effects on labor productivity of 3.6% over five years, driven by modest employment reductions alongside stable or growing revenue" 53: A Polish team tries to test Peter Turchin’s equations for predicting political unrest on recent Polish history, has to make some changes but claims mostly positive results. 54: New big multi-author Substack, The Argument, trying to be a sort of center-left version of the model pioneered by The Free Press and other high-production-value ideological Substack properties. Excited to see Kelsey Piper is involved, and she starts off strong with a post on the latest round of First World basic income studies, which find few positive effects. This is surprising, because recipients didn’t waste the money on alcohol or gambling or anything - they paid down debt and got useful goods. Still, it didn’t even affect things that should have been obvious, like stress level. It’s not even clear that amounts of money large enough to help with rent made homeless people more likely to get houses! Matt Bruenig criticizes the article, accusing Kelsey’s studies of being downstream of Perry Preschool style dreams that exactly the right welfare program will have massively compounding effects that cut poverty out at the root and turn everyone into elite human capital; he thinks giving people money won’t do this, but it will increase equality and give the poor better lives. I assume he’s not a strong hereditarian, but his argument makes even more sense from that perspective, and I’ve certainly criticized dumb outcome measures like infant brain waves which we have only tenuous reasons to think are related to anything we care about. But Kelsey reasonably responds that the outcome measures she’s talking about include stress level and life satisfaction. To defuse this critique, Bruenig either has to argue that our construct “life satisfaction” doesn’t really measure whether someone’s life is satisfactory, or else claim that giving poor people satisfactory lives isn’t really what we’re going for - which I think would require more explanation on his part. There’s some further (impressively acrimonious) debate on X, but I don’t see anything that addresses my core concern. GiveDirectly, a charity involved in basic income experiments, has a presponse here; they say that some studies are positive, and that the ones that aren’t might have tried too little cash to matter, or been confounded by COVID making everything worse. They also point out that basic income is harder to study than traditional programs like giving people housing, because if you’re giving housing you can measure housing-related outcomes directly and have a pretty good chance of getting enough statistical power to find them, but since everyone spends cash on different things, the positive effects might be scattered across many different outcomes (and therefore too small to reach significance on each). Everyone involved in this debate wants to emphasize that the poor results are for First World studies only, and that studies continue to show large benefits to giving cash in the developing world. 55: Related: I was less impressed by The Argument’s first foray into housing policy, which follows an all-too-familiar pattern: Some people say they don’t like noise and disorder and try to make rules against it in their apartments.
X-men

X-men is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 16, 2024 and August 16, 2024. The archive places it in contexts such as "in the X-men comic books". It most often appears alongside 20th Century Fox, Abomination, Abomination.

Reference entry
X-men
Mention count
1
Issue count
1
First seen
August 16, 2024
Last seen
August 16, 2024
August 16, 2024 · Original source
Given Marvel Comics, why Silver Age (1961-1965)? I.a. Why Superhero Comic Books? The winner of last year’s Astral Codex Ten book review contest was Brandon Hendrickson. Brandon wrote about Kieran Egan’s The Educated Mind. One of the foundations of Egan’s educational philosophy is that people learn through stories. He believes early education should focus on teaching lessons through myths and legends. This matches my experience. My kids’ favorite podcast is Greeking Out – a very well produced, very entertaining, National Geographic podcast about Greek Legends. Aside #1: When my oldest daughter was three years old she would ask everyone she met “Do you know any myths? Can you tell me a myth?” She especially liked asking people from different places to get myths from their local cultures. Once, she asked the question to a friend of mine who grew up in South Africa, “Can you tell me any South African myths?” He struggled for a minute and then said, “Okay! I have one! Bread never falls butter side down!”. That was not the type of myth she was looking for; nor the type of myth we will be discussing in this review. Every culture has foundational myths. These stories are entertaining and engaging, but they also teach valuable lessons about both what is important in that culture, and how people in that culture are expected to behave (or at least the Platonic Ideal of how they should behave). In the modern, Western world, we have assimilated many of these foundational stories, particularly the Greek myths. My kids definitely know the Greek myths, but they also know elements of Norse mythology, Egyptian myths, stories about Anasi from West Africa and more. More fundamentally my wife and I, while not religious ourselves, have made a point of exposing the kids to the stories from the Bible. It is not politically correct to call Biblical stories “myths”, but they serve the same purpose – shared cultural understanding of the way the world works. My wife grew up without any religion, and when she was in high school, she struggled with the metaphors and religious allegories that were omnipresent in most of the Western canon. In our culture, familiarity with the Bible is important for an educated person – whether they are religious or not – because it is the foundation of so much of the rest of our culture. I believe the other set of mythological stories that are foundational to our culture are – and by this point I am sure you see where I am going here – comic book superheroes. If true, then having more than a surface-level understanding of the most important superhero stories is important in a similar way to that knowing the Bible stories is important. “Do unto others as you would have them do unto you” is an important idea to understand. So is, “With great power comes great responsibility”. I.b. Why Marvel? While there are many independent superheroes that are not owned by major conglomerates, the superheroes who have built our modern foundational myths are currently owned by two corporations. Warner Bros. Discover owns the DC library of superheroes including Superman, Batman and Wonder Woman. In 2009 Disney purchased Marvel Comics and took ownership of their characters, including Spiderman, X-men and the Avengers. Aside #2: Marvel has sold temporary film rights to many of their characters over the years. The most relevant sales started in 1994 when Marvel sold the film rights of X-men and mutants to 20th century Fox, then in 1996, when Marvel went bankrupt, Fox picked up the rights to the Fantastic Four (and New Line picked up Blade). In 1999 Marvel sold the film rights (and live action TV, and animated TV longer than 44 minutes) of Spider-man and related characters to Columbia Pictures (part of Sony) for $7MM. Marvel actually attempted to sell ALL of their remaining Marvel IP film rights to Sony for $25MM, but the top management at Sony was not interested. Sony’s management allegedly told their chief negotiator “Nobody gives a shi*t about any of the other Marvel characters. Go back and do a deal for only Spider-Man). Disney acquired Marvel in 2009, and then Fox in 2019, bringing the two separated packages of characters all back together under one roof (Blade reverted back to Marvel in 2012). Sony still owns the rights to Spider-man but has made a deal with Disney to include some of his films within the Marvel-Disney universe. Marvel sold the film rights of The Hulk to Universal in 1990 and the current status of that agreement is complicated (the consensus is that Marvel now controls the film rights to the character, but Universal owns distribution rights to any stand-alone Hulk film, which could be why Disney let's Hulk co-star in Thor movies, but not vice versa). In the early aughts Marvel wanted to build their own film franchise, but were limited to only using their remaining “B-list” characters – Spider-man, X-men, and the Fantastic Four were all off limits. Fortunately, Kevin Feige, president of production for Marvel at the time, saw a way forward. He convinced Ike Perlmutter, Marvel CEO, to allow for the production of a series of films with the remaining characters begining with Iron Man (2008). Jon Favreau directed and cast Robert Downey Jr as Tony Stark. The film blew away expectations. Kevin’s plan of a series of movies where the characters would interconnect was suddenly feasible. Iron Man was followed by The Incredible Hulk, Thor, and Captain America: The First Avenger. None managed the box office magic of Iron Man, but all were successful enough that the plan stayed on track. In 2012 the characters were all brought together in the first Avengers film, which opened to over $200MM domestically and went on to gross more than $1.5B (which made it the 3rd highest grossing film of all time). Marvel became the first studio to take the interconnected world of their comic books and make the model work on the big screen (for a much larger audience). Once the model was proven to work, other studios tried to duplicate it. Aside #3: Warner Bros’ stumbles with the DC shared universe of Batman, Superman and the Justice League are well known, but that was actually their SECOND attempt at a shared universe. Their first attempt tried to copy the Marvel method more closely. They chose their own B-list hero and set up his first film to allow for a wider mythology. Alas Green Lantern (2011) failed at the box office and we never got stand-alone films about Sinestro (Yellow Lantern), Carol Ferris (Star Sapphire, the Violet Lantern), John Stewart (African American Green Lantern), Kyle Rayner (1990s Green Lantern), Alan Scott (original Green Lantern), or the Blue, Red, and Orange Lantern Corps. At least so far, no studio has successfully created anything with close to the traction obtained by the Marvel Cinematic Universe (MCU). Warner’s DC Extended universe (DCEU) had trifling success, but is being shelved and rebooted for a fresh attempt next year. Universal’s attempt at a “Dark Universe” kicked off with Tom Cruise in The Mummy (2017), but was dead on arrival. Paramount’s attempt to link the Transformers Universe to GI Joe at the end of Transformers: Rise of the Beasts has been appropriately mocked. Sony’s Spider-man films linked to the MCU have been very successful, but their attempt at a stand-alone non-MCU Spider-man universe using Spider-man’s villains as anti-heroes has floundered (mostly succeeding only as a source of memes). Next Mattel will be attempting to build a universe off the success of last year’s Barbie and may include Polly Pocket, American Girl, Hot Wheels, and He-Man and the Masters of the Universe (no word yet on Thomas the Tank Engine, View Master and the Magic-8 Ball, but all are apparently in development). To date, only Marvel has successfully built a “Cinematic Universe”. One potential reason for the MCU’s success is that Kevin Feige built his cinematic universe on the back of the existing interconnected universe of the comics. But those comics were not the first interconnected universe of stories. For that we would need to go back to our foundational myths. The Bible stories mostly interconnect. Adam and Eve flows into Cain and Abel. David and Goliath leads to the Wisdom of Solomon. Greek Myths DEFINITELY interconnect. Supporting characters in one Greek myth have starring roles in their own stories. The Greek pantheon of tales even have their own version of the Avengers. In the Quest for the Golden Fleece, Jason brings together the Argonauts, who included in their number Theseus (who defeated the Minotaur), Orpheus (who braved the underworld) and Hercules himself – all A-list stars in their own “franchises”. Stand alone stories that exist within an interconnected universe are rare in modern media but were common in the ancient myths that have stood the test of time. Only Marvel has successfully created a shared universe that follows the pattern of ancient myths. Only Marvel films have stand-alone stories and protagonists who exist together in an interconnected world. Something about that method of storytelling is deeply pleasing for humans across many cultures. Marvel films are the first and most successful modern version of the mythological universe, and that it is worth spending more time exploring Marvel’s underlying mythology and where it came from. I.c. Why 1961? The origins of Christianity and Judaism (and Buddhism and Hinduism) are very murky. Even Islam is far enough in the past that we only have a very rough understanding of how it came to exist. When scholars want to understand in detail how a new religion is born they are far better to look at Mormonism or, if you accept it as a religion, Dianetics. Similarly, we have versions of Greek myths that have been passed down to us, but we can never know how those myths changed from their first telling to their “final” versions. Were the stories once unrelated, and only later became crafted into a single “universe”? Or were the stories built off each other one by one (“Dad that Golden Fleece story was amazing! Do you know any other stories about the Hercules guy?”)? Or was it something in between? Perhaps the stories all existed independently, but were later crafted together (“Remember that 12-labors story I told you? Actually that was the same guy who was on the Argo!”) Unlike Greek legends, we can know the origin of the Marvel Universe. We can see how it was constructed step-by-step. The people who did it (most importantly Stan Lee, Jack Kirby, and Steve Ditko) are dead now, but they have not been dead for long. We can read the original work, see how it changed over the last 60 years, and we can ask the creators “what were you thinking at the time” (or at least read their answers from old interviews). We can’t always trust what Stan Lee says, but at least we can hear his point of view. No one has a transcript of an interview with Homer, or knows exactly what he was thinking when he called it the “wine-dark sea”. Tl;dr: Why read about Marvel Comic superheroes 1961-1965? Because interconnected mythological stories are very important to cultures, Marvel is the leading contender of the most recent modern mythology, and it originated in the first half-decade of the 1960s. II. How did Marvel Superhero Comics happen? Timely Comics published their first comic book in 1939 and called it “Marvel Comics”. Their most popular World War II comics included Captain America, the Human Torch (an android unrelated to the modern Human Torch except in powers, appearance and name), and Namor, the Submariner. In the early 1950s superheroes became less popular, so Timely changed its name to Atlas Comics and focused on humor, western, horror, war and science fiction stories. But in 1956 DC Comics began re-introducing their Golden Age superheroes and, in the second half of the 1950s, the genre took off again – particularly Superman, whose title, Action Comics, became the number one selling comic in America. Stan Lee, editor and chief at Atlas at the time, wanted to get in on the superhero action. Unfortunately in 1957 Atlas lost its distributor and the company had to rely on “Independent News” to get its comics on newsstands. The complication was that Independent News was owned by “National Periodical Publications”, who also owned DC-comics and did not want Atlas to introduce superheroes to compete with Superman, Green Lantern and the Flash. Independent News agreed to distribute Atlas comics but limited the publisher to eight titles per month, and only in non-super hero genres (like horror, romance and science fiction). Blocked from creating and launching new superhero titles, Stan Lee got creative, and in August 1961 Atlas Comics published Fantastic Four #1. Aside #4: Fantastic Four #1 was on newsstands in August 8th, 1961, but the date on the cover was November 1961. The convention at the time was that the cover date was not the “publication date” but rather the “pull date”. The pull date was the time when the retailer could send back unsold copies back to the publisher for a refund. In fact the retailer did not need to send the entire issue back, just the cover, as it was assumed that comic books could not be sold without the cover, and it saved on postage. This was only relevant because it was great for my dad who was a child at the time. My dad was friends with the kid whose father owed the local pharmacy which meant he had access to every comic book published in the late 1950s as long as he was willing to wait a few months and read it without a cover. Going forward in this essay I will always use the pull dates rather than the publication dates for individual comic book issues as they are far easier to source. If you want to convert pull dates back into publication dates you can subtract roughly two months, but it is inconsistent and sometimes longer, as was the case with Fantastic Four #1. Check out the cover of Fantastic Four #1: To the modern eye this certainly looks like a superhero comic. Four heroes with super powers fighting a giant monster. But in the eyes of publishers in 1961 this looked more like a science fiction adventure comic than something that would go head to head with Superman. Here are the covers of Action Comics (the best selling superhero comic at the time) from the three months leading up to Fantastic Four #1: Notice what they have in common? “Super Rivals”, “Super revenge”, “Super Substitutes”. And all include Superman in his blue and red tights. Fantastic Four’s cover featured super powers, but never used the word “super” and no one was wearing superhero costumes. Fantastic Four, as a superhero story, slipped under the radar because it wasn’t really a superhero story at all. It was a story about four close friends who attempted to fly into space, but then something goes wrong and they crash back to Earth. The experience changes them and they decide they now need to use their new abilities to help the rest of humanity – specifically against monsters who are invading from under the Earth. It is a fantastical science fiction story – not a superhero story. Later in his career Jack Kirby, the illustrator of the issue and co-creator of the Fantastic Four, was asked about his inspiration for the Fantastic Four heroes. He did NOT say Superman – or any superhero. He said Challengers of the Unknown. Challengers of the Unknown was an adventure story co-created by Kirby in Showcase #6 in February 1957. Here is how Wikipedia describes the Challengers origin: When acquaintances miraculously survive a plane crash unscathed, they conclude that since they are "living on borrowed time" they should band together for hazardous adventures. The four—pilot Kyle "Ace" Morgan, daredevil Matthew "Red" Ryan, strong and slow-witted Leslie "Rocky" Davis, and scientist Walter Mark "Prof" Haley—became the Challengers of the Unknown. Showcase #6, and the first appearance of the Challengers of the Unknown, by Jack Kirby Visually the Challengers and the Fantastic Four were similar. Both wore skin tight uniforms with belts and minimal decoration. The Fantastic Four’s relatively simple characterizations were practically pulled from Challengers. Reed takes on the traits of both Kyle, the leader, and Walter, the scientist. Johnny, the Human Torch is the daredevil. The Thing is “strong and slow-witted”. Sue, the only woman on the team, seems like a new addition, but is likely based on June Robbins who joined the Challengers team in Showcase #7, as an “honorary” or “girl-Challenger”. After surviving their respective “miraculous” crashes, both the Challengers and the Fantastic Four band together to help the world. They both travel through space and other dimensions, fighting mad scientists and monsters. The Fantastic Four’s early antagonists were not traditional super villains. In the first few issues they fight monsters from under the Earth (Issue #1), shape changing aliens (#2), and a charlatan who uses hypnotism to steal from his audience (#3). In issue #4 Kirby and Lee re-introduce Namor, the Submariner, one of Marvel’s top IP from the 1940s, and have him kidnap Sue. Only in Issue #5 and #6 (June and August 1962) and do we get a more standard-supervillain when Dr Doom attempts to steal the Fantastic Four headquarters and throw it into space. The next superhero Lee created was even less heroic than the Fantastic Four. In April 1962 (pull date), Marvel published The Incredible Hulk. If it was even a superhero story in disguise it was a very good disguise. The story was a scientific-filtered version of Dr Jekyl and Mr Hyde. It was a pure monster-story with nothing very super about it. Nothing on the cover suggests this has anything to do with superheroes: It is not clear if even Lee at the time thought the Hulk would be a superhero. In Fantastic Four #5 Johnny is reading a “great new comic mag” and mocks the Thing by comparing him to the Hulk. It seems pretty clear at this point that in the Fantastic Four’s world, the Hulk is just a fictional comic book, like in ours (more on that later): The other two superheroes the Marvel introduces in this period have even more subtle introductions. At the time Marvel had a number of generic-sounding titles and told science fiction and fantasy stand-alone stories: Tales to Astonish
By early 1963 it was established that the Fantastic Four, the Hulk and Spider-man all existed together within the same shared universe. But what about Ant Man,Thor and Iron Man? Aside #5: The Hulk comic in Fantastic Four #5 pretty clearly establishes that the Hulk was a fictional character in the Fantastic Four world, but there are other clues that Lee was not thinking about his characters as existing and crossing over in the early days. Both Bruce Banner (the Hulk) and Mr Fantastic fight off global alien invasions in their early issues. In both cases the stories make clear that only Bruce/Reed is smart enough to save the world. No mention is made of the OTHER scientist who saved the world from the alien invasion a few months earlier. Bringing different superheroes from their own titles together was not an idea created by Atlas/Marvel and Lee. That was likely All Star Comics #3 (December 1940) when writer Gardner Fox brought together all the major DC heroes who were not staring in their own independent titles, including Green Lantern, the Flash and Doctor Fate, to create the Justice Society of America (JSA). Batman and Superman cameoed in All Star Comics #7, but generally they were considered too popular to dilute their appearances in ensemble titles. That changed in March 1960 when DC re-launched the idea of a superteam with the Justice League of America and included all of their most popular heroes as the leads – Superman, Batman and Wonder Woman. It was immediately a top seller. The launch of JLA is likely what caused the owner of Atlas to ask Lee to create a ”superhero team comic”. Lee did not have a stable of heroes to bring together, so he had to create something entirely new – The Fantastic Four. But now that Lee DID have a collection of his own heroes AND he had the greenlight to create straightforward superhero comics, he decided to build himself his own JLA. In September 1963 Atlas published two new titles: The Avengers and the X-men. The X-men were a brand new team of all new heroes, but the Avengers were a close parallel to the Justice League. Lee took his existing collection of heroes (except the Fantastic Four and Spider-man) and created an excuse for a team-up. In the issue they individually battle Thor’s brother Loki before coming together to defeat him as a team. They decide that given they all have different powers, they should work together to be unstoppable. The entire formation of the team takes only four panels and is a little corny, but it does its job: While the Avengers were a clear copy of the Justice League, Stan Lee put his own spin on it. While the JLA superheroes all had roughly the same personality and no real inter-team conflict, Lee made his heroes very distinct – almost caricatures – and there was PLENTY of inter-team conflict. The Hulk in particular abandoned the team in the second issue and was the primary antagonist by Avengers #3. Avengers #3 (January 1964) is itself the final step in connecting all of the Marvel heroes together. The Hulk has gone missing and the rest of the team wants to find him. Iron Man uses an “Image Projector” to ask other superheroes around the world if they had seen the Hulk. He visits the Fantastic Four, Spider-man and the X-men. In that same month in Tales of Suspense, Iron Man meets Angel (one of the X-men). The cat was out of the bag. Lee had a new trick to boost sales of all of his titles and he put it to work throughout the year. The first full crossover of the Fantastic Four and the Avengers happens in May (Fantastic Four #26). Daredevil premiered in March 1964 (with Spider-man on the cover, but not in the pages), and crosses over in Amazing Spider-man #16 (September 1964). Dr Strange first appears on the cover of another title in Fantastic Four #27 (June 1964). The Avengers battle the X-men (before teaming up) in X-men #9 (Dec 1964) Atlas was no longer just a collection of comic books about various topics, or even a collection of different flavors of superhero. It was a single shared universe: The Marvel Universe. It wasn’t planned out in advance, instead it happened in stages due more to commercial rather than artistic needs. Basically Stan Lee created the most successful modern mythology because he needed the money. III. Are Silver Age Marvel Comics any good? Well, apart from Amazing Spider-man, which holds up surprisingly well, I would not recommend reading any of them. Even Spider-Man is much weaker than the Ultimate Spider-Man reboot version of the story published 2000-2011. If you wanted to read Spider-Man from the beginning you would likely enjoy that later series a lot more than the original. The other titles vary in quality from “okay” (the Fantastic Four) to “absolute garbage” (Ant Man stories in Tales to Astonish). Which begs the questions, if these comics were so bad, how did they succeed as well as they did? Clearly the comics were “good for their time”. Millions of people bought and read them, and they clearly passed the “test of time”. So does that mean that we are better today at making art than we were back then? Or is art neither better or worse, just “of its time” and people back then would think the Ultimate Spider-man stories from 2000 were unreadable? I will argue the following: The stories were “good for their time”. VERY good for their time. They were much much better than the comic book stories that preceded them, and much better than other contemporary comic book adventures (like those being published by DC)
While the Avengers were a clear copy of the Justice League, Stan Lee put his own spin on it. While the JLA superheroes all had roughly the same personality and no real inter-team conflict, Lee made his heroes very distinct – almost caricatures – and there was PLENTY of inter-team conflict. The Hulk in particular abandoned the team in the second issue and was the primary antagonist by Avengers #3. Avengers #3 (January 1964) is itself the final step in connecting all of the Marvel heroes together. The Hulk has gone missing and the rest of the team wants to find him. Iron Man uses an “Image Projector” to ask other superheroes around the world if they had seen the Hulk. He visits the Fantastic Four, Spider-man and the X-men. In that same month in Tales of Suspense, Iron Man meets Angel (one of the X-men). The cat was out of the bag. Lee had a new trick to boost sales of all of his titles and he put it to work throughout the year. The first full crossover of the Fantastic Four and the Avengers happens in May (Fantastic Four #26). Daredevil premiered in March 1964 (with Spider-man on the cover, but not in the pages), and crosses over in Amazing Spider-man #16 (September 1964). Dr Strange first appears on the cover of another title in Fantastic Four #27 (June 1964). The Avengers battle the X-men (before teaming up) in X-men #9 (Dec 1964) Atlas was no longer just a collection of comic books about various topics, or even a collection of different flavors of superhero. It was a single shared universe: The Marvel Universe. It wasn’t planned out in advance, instead it happened in stages due more to commercial rather than artistic needs. Basically Stan Lee created the most successful modern mythology because he needed the money. III. Are Silver Age Marvel Comics any good? Well, apart from Amazing Spider-man, which holds up surprisingly well, I would not recommend reading any of them. Even Spider-Man is much weaker than the Ultimate Spider-Man reboot version of the story published 2000-2011. If you wanted to read Spider-Man from the beginning you would likely enjoy that later series a lot more than the original. The other titles vary in quality from “okay” (the Fantastic Four) to “absolute garbage” (Ant Man stories in Tales to Astonish). Which begs the questions, if these comics were so bad, how did they succeed as well as they did? Clearly the comics were “good for their time”. Millions of people bought and read them, and they clearly passed the “test of time”. So does that mean that we are better today at making art than we were back then? Or is art neither better or worse, just “of its time” and people back then would think the Ultimate Spider-man stories from 2000 were unreadable? I will argue the following: The stories were “good for their time”. VERY good for their time. They were much much better than the comic book stories that preceded them, and much better than other contemporary comic book adventures (like those being published by DC)
X-men #12

X-men #12 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 16, 2024 and August 16, 2024. The archive places it in contexts such as "featured in X-men #12 and #13". It most often appears alongside 20th Century Fox, Abomination, Abomination.

Reference entry
X-men #12
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August 16, 2024
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August 16, 2024 · Original source
The two-part story featured in X-men #12 and #13 is one of the best X-men of the era. In the two-parter we find the team locked up in the X-mansion trying to prepare for the arrival of the unstoppable Juggernaut. There is a sense of dread that there is nothing the team can do to stop him, only slow him down. While they are waiting for the inevitable, Professor X tells the team his backstory and how the Juggernaut is actually his step brother with an old grudge. The Professor tells his students about how, when he was younger, he used to be an amazing athlete. Kirby draws images of the teenage Professor running track, playing football and winning trophies. But then his stepbrother, Cane (who later becomes the Juggernaut) takes him on a drive through the mountains, drives the car off the cliff and jumps to safety. Charles is still in the car as it plummets off the mountains. His students ask “Was... that how you lost use of your legs, Professor?”. It was clearly intended to be. It would have been a powerful moment.
X-men #13

X-men #13 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 16, 2024 and August 16, 2024. The archive places it in contexts such as "featured in X-men #12 and #13". It most often appears alongside 20th Century Fox, Abomination, Abomination.

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X-men #13
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August 16, 2024
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August 16, 2024 · Original source
...ed Lucifer to be the cause of the paralysis. It was miscommunication. Kirby had a plan for Professor X’s origin, but it wasn’t coming until issue #12. The two-part story featured in X-men #12 and #13 is one of the best X-men of the era. In the two-parter we find the team locked up in the X-mansion trying to prepare for the arrival of the unstoppable Juggernaut . Ther...
X-men #3

X-men #3 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 16, 2024 and August 16, 2024. The archive places it in contexts such as "In X-men #3 the Professor is thinking to himself about how he is in love with Jean Grey". It most often appears alongside 20th Century Fox, Abomination, Abomination.

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X-men #3
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August 16, 2024 · Original source
In X-men #3 the Professor is thinking to himself about how he is in love with Jean Grey – the 16 year old newest member of the team. The panel:
X-men #9

X-men #9 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 16, 2024 and August 16, 2024. The archive places it in contexts such as "X-men #9 (Dec 1964)"; "in X-men #9 the X-men and the Avengers team up"; "Lee’s mistake in X-men #9 came back to haunt him". It most often appears alongside 20th Century Fox, Abomination, Abomination.

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X-men #9
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August 16, 2024
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August 16, 2024
August 16, 2024 · Original source
While the Avengers were a clear copy of the Justice League, Stan Lee put his own spin on it. While the JLA superheroes all had roughly the same personality and no real inter-team conflict, Lee made his heroes very distinct – almost caricatures – and there was PLENTY of inter-team conflict. The Hulk in particular abandoned the team in the second issue and was the primary antagonist by Avengers #3. Avengers #3 (January 1964) is itself the final step in connecting all of the Marvel heroes together. The Hulk has gone missing and the rest of the team wants to find him. Iron Man uses an “Image Projector” to ask other superheroes around the world if they had seen the Hulk. He visits the Fantastic Four, Spider-man and the X-men. In that same month in Tales of Suspense, Iron Man meets Angel (one of the X-men). The cat was out of the bag. Lee had a new trick to boost sales of all of his titles and he put it to work throughout the year. The first full crossover of the Fantastic Four and the Avengers happens in May (Fantastic Four #26). Daredevil premiered in March 1964 (with Spider-man on the cover, but not in the pages), and crosses over in Amazing Spider-man #16 (September 1964). Dr Strange first appears on the cover of another title in Fantastic Four #27 (June 1964). The Avengers battle the X-men (before teaming up) in X-men #9 (Dec 1964) Atlas was no longer just a collection of comic books about various topics, or even a collection of different flavors of superhero. It was a single shared universe: The Marvel Universe. It wasn’t planned out in advance, instead it happened in stages due more to commercial rather than artistic needs. Basically Stan Lee created the most successful modern mythology because he needed the money. III. Are Silver Age Marvel Comics any good? Well, apart from Amazing Spider-man, which holds up surprisingly well, I would not recommend reading any of them. Even Spider-Man is much weaker than the Ultimate Spider-Man reboot version of the story published 2000-2011. If you wanted to read Spider-Man from the beginning you would likely enjoy that later series a lot more than the original. The other titles vary in quality from “okay” (the Fantastic Four) to “absolute garbage” (Ant Man stories in Tales to Astonish). Which begs the questions, if these comics were so bad, how did they succeed as well as they did? Clearly the comics were “good for their time”. Millions of people bought and read them, and they clearly passed the “test of time”. So does that mean that we are better today at making art than we were back then? Or is art neither better or worse, just “of its time” and people back then would think the Ultimate Spider-man stories from 2000 were unreadable? I will argue the following: The stories were “good for their time”. VERY good for their time. They were much much better than the comic book stories that preceded them, and much better than other contemporary comic book adventures (like those being published by DC)
Kirby had apparently told Lee that he was going to incorporate a villain who had been responsible for the crippling of the Professor. Kirby either was not clear to Lee on which villain it was, or Lee did not remember, but the result was when in X-men #9 the X-men and the Avengers team up to defeat an alien named Lucifer, Lee drops in some dialog on the second to last panel where Charles tells the group that the villain, Lucifer, was responsible for the loss of his legs. The panel:
Lee’s mistake in X-men #9 came back to haunt him. Rather than ignore the panel he had written a few months earlier, he doubled down and explained how, while it would have been dramatically appropriate if he had lost use of his legs from Juggernaut, unfortunately that could not be the case due to continuity concerns. The Professor replies to his students:
Xiao 2021

Xiao 2021 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 09, 2024 and April 09, 2024. The archive places it in contexts such as "Then turns out they’re sold in the market (Xiao 2021)". It most often appears alongside #S14, 2009 flu pandemic, 2013-16 West African Ebola outbreak.

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Xiao 2021
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April 09, 2024
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April 09, 2024 · Original source
Suppose you know that one of the animals in the middle crate on the right was caught in some safe, disease-free way, 500 km away, three months ago. How confident does that make you feel? To answer the question about which animals in the Xiao paper are plausible: at least civets and bamboo rats. SARS spread back and forth in some kind of weird net between civets, raccoon dogs, and a bunch of made-up-sounding animals like "ferret-badgers" and "greater hog-badgers". For all we know, COVID could have done likewise. If all of this sounds desperate and wishy-washy, imagine an alien who comes to Earth, hangs out at Area 51, and catches COVID. She theorizes that she got it from humans. She’s heard that the humans at Area 51 came from schools, so she abducts fifteen humans from a nearby school and gives them COVID throat swabs. None of them are positive, so she announces that humans can’t be a COVID intermediate host. Other aliens suggest further testing, but she has already vaporized Earth, just in case, so the further testing never gets done. Simon added: Even the strongest proponents of the raccoon dog hypothesis have walked back their bold claims that raccoon dogs are the host. I asked a scientist whose name is on some of the original raccoon-dog papers if this was true. He said: I secretly root for other intermediate hosts. Bamboo rats or civets would be really fascinating and have flown under the radar. But it’s been really hard to bet against raccoon dogs. First we learn they can transmit and the virus didn’t change when transmitted between them (Freuling 2020)? Then turns out they’re sold in the market (Xiao 2021)? Then it turns out they’re freaking everywhere in the genetic data from the market, the most common mammal detected? Then it turns out the market animals aren’t from northern China fur farms? It’s been a tough road for those betting against them…. 1.3: 92 Early Cases There was a long multi-branching thread of arguments centered around 92 early cases, for example here: My understanding of the situation: the first officially-confirmed case of COVID started December 11, 2019. Later in the pandemic, in 2021, the World Health Organization wanted to figure out if that was really the first, or whether there had been earlier ones. They scoured Chinese hospital records for illnesses that might be COVID during the two months before the official discovery (ie early October to early December) In particular, they asked Wuhan hospitals for records of any cases of fever, flu, respiratory illness, and pneumonia. The hospital gave them 76,253 cases, because China is big and flu is common. This was slightly more cases than usual, but there was a normal flu spreading too, so the researchers didn’t find this very compelling. Then they narrowed these cases down to those that were “clinically compatible” with COVID, and ended up with 92. Then they went over those 92 more carefully, including “review by the external multidisciplinary clinical team” and blood draws from the former patients. They were able to track down 67 of the 92. The clinical team decided none of those 92 cases really resembled COVID, and the blood draws were all negative. They published this as the results of their study: The retrospective search for cases compatible with COVID-19 illness identified 76 253 episodes with one of four indicator conditions. A rise in one of these conditions, [acute respiratory illness] (as well as [flu-like illness] and fever), was seen in this group of individuals in the over-60-year age group in early December. The clinical assessment of the 76,253 individuals revealed 92 cases clinically compatible with COVID-19. It is possible that the application of stringent clinical criteria, resulting in the identification of only 92 clinically compatible cases, may have decreased the possibility of identifying a group or groups of cases with milder illness. All the 92 cases were rejected as cases of SARS-CoV-2 infection on further clinical review. None of these cases (where blood could be obtained) was positive on SARS-CoV-2 serological testing carried out more than 12 months later. The use of retrospective serological testing so long after the illness cannot be relied on to exclude the possibility of SARS-CoV-2 infection at the time of the presenting illness, given the possible drop in SARS-CoV-2-specific antibody over time and the associated reduced sensitivity of commercial assays. The possibility that earlier transmission of SARS-CoV-2 infection was occurring in this community cannot be excluded on the basis of this evidence. In other words “we looked for early COVID, we didn’t find any, but we can’t promise we didn’t miss anything”. On Twitter, Giles Demaneuf makes an interesting point. The researchers took the samples in 2021, when China was in Zero COVID. When the Wuhan outbreak was finally contained in early 2020, 4.4% of Wuhanites had contracted COVID. So isn’t it surprising that 0/67 of the former patients who the researchers tested were had antibodies to COVID? The chance that 67 randomly-selected people in a population with 4.4% prevalence rate are all negative is only about 5%. Is this evidence of foul play? No. See the conclusions section of the report, which said: “The use of retrospective serological testing so long after the illness cannot be relied on to exclude the possibility of SARS-CoV-2 infection at the time of the presenting illness, given the possible drop in SARS-CoV-2-specific antibody over time and the associated reduced sensitivity of commercial assays”. You have a lot of COVID antibodies just after getting COVID. By a year or so afterwards, you might not have enough to detect. So it’s not surprising the WHO study didn’t detect any. Why did they even try looking for antibodies? There seem to be two reasons not to: first, they should have known antibodies would decay after a year. Second, even if some of them did have antibodies, how would we know they weren’t just infected in spring 2020 like everyone else? They don’t say. My guess: antibody decay is very variable. Some people’s antibodies might last more than a year. So if they found that way more than 4.4% of people had antibodies, that would be surprising and suggest that most of them had had COVID in autumn 2019. But instead they found that nobody had antibodies, which is consistent with one or two of them getting sick when everyone else got sick, and having their antibodies decay at the normal rate. But also, I think the antibodies were just intended to supplement the clinical review, and not be a very important part of their determination. I think this study is moderately strong evidence that there wasn’t much COVID going around before December 2019. Doctors looked for cases, they winnowed them down into the cases that looked most like COVID, but when they examined those cases closely, they didn’t look enough like COVID to be interesting. I don’t think the antibody tests add or subtract much from this assessment. I would be fine if someone else said they don’t think the WHO report provides much evidence either way. The main thing I want to insist on is that there’s no conspiracy to hide 92 previously-undiscovered cases. They searched really hard for potential cases, they subjected the most plausible candidates for further review, and then they decided those ones were not, in fact, COVID. (You can read all of this here. It’s not a very good description and I’d be interested if someone has a more thorough writeup of the research.) This was just one of many efforts that researchers made to try to identify pre-December-2020 COVID cases. For example, 30,000 people donated blood in autumn 2019, and the hospitals still had most of it. So they tested the blood samples for COVID antibodies and didn’t find any. I don’t think antibodies decay in stored blood samples (I might be wrong). There are 12 million people in Wuhan, so if even a few hundred people had COVID during that time, one of them should have turned up. None of them did. Finally, during COVID’s officially-recognized existence, its numbers doubled about once every 3.5 days. Again, if COVID existed a month earlier than previously believed, then it would be 256x more common than expected. This would be hard to miss! Nobody found evidence from excess mortality that COVID was 256x more common than expected. I’m using the version of the doubling time argument because it’s simple enough for me to understand, and I don’t have to worry about anyone trying to hide something in their complex model. It’s not exactly true, but it’s true enough to rule out COVID starting much before November 2019. If you want the fancy official version, it’s in Pekar 2021 and looks like this: This alone isn’t fatal to lab leak. It’s perfectly possible for the lab to leak (let’s say) November 5th, the virus spreads a bit, and then a month later someone goes to the wet market, coughs on a vendor, and starts the officially recognized pandemic. But if that were true, you’d expect (let’s say) 30 cases by early December. Let’s say the wet market vendor was exactly Case # 30. She infected the other wet market vendors, starting a pandemic with an obvious center at the wet market and lots of infected wet market vendors and patrons. What about Case # 29? If they were (let’s say) a barista, how come they didn’t infect people at their coffee shop? How come there wasn’t a second obvious cluster radiating out from a coffee shop, lots of coffee-shop-linked cases, etc? How come there weren’t 30 equally-sized clusters? In order to avoid this, you either need to claim that the wet market was a perfect superspreader location, or that the pattern with lots of cases in the wet market and few-to-none anywhere else was a result of ascertainment bias. Saar made both those arguments during the debate, but I thought Peter rebutted them effectively. 1.4: COVID in Brazilian wastewater Nicholas Halden (blog) writes: What should we make of this study, which found the presence of covid in Brazilian wastewater in late 2019? Consider the doubling times. The study says that scientists working in late 2020 found COVID in samples of Brazilian wastewater from November 27, 2019. This was long before the first detected case of transmission in Brazil on March 13, 2020. Between November 27, 2019 and March 13, 2020 is about 16 weeks, so 32 COVID doubling times. 32 doubling times with no lockdown is enough time for COVID to infect every single person in Brazil. If COVID had infected everyone in Brazil before the first recognized case, we would have noticed. (again, COVID doubling time isn’t exactly invariably 3.5 days, but here we’re talking about numbers big enough that the exact details don’t matter very much) So if COVID was in Brazil on November 27, it must have fizzled out instead of going pandemic. How likely is that? If one person had COVID, it’s not too unlikely - not all COVID cases transmit it forward. If (let’s say) twenty people had COVID, it’s very unlikely - at that point, the law of large numbers takes over; in a freak coincidence, every single patient would have to fail to infect anyone else. So almost certainly fewer than 20 people in Brazil had COVID in November 27. So which is more likely - that somehow 20 people had COVID long before the virus was officially detected, and on a totally different continent, yet somehow a scientist looking through wastewater found the water from exactly those people and managed to detect the virus? Or that there was a sampling error, which happens all the time in these kinds of things? Peter wrote a blog post on some of these issues. He found that there were positive tests from wastewater samples as early as March 2019, which doesn’t fit anyone’s timeline, including lab leakers’. And most of these positives (including the Brazilian sample) contained later strains of the virus with mutations it picked up late in 2020. So these were almost certainly false positives from contamination. 1.5: Biorealism’s 16 arguments Biorealism has a list of sixteen arguments, which he liked so much that he posted it three times in the ACX comments, twice on Less Wrong, twice on Manifold, and about a dozen times on Twitter under multiple account names. Some posts were slightly different from others, but a typical version is: Importantly, Miller incorrectly claimed the N501Y mutation would result from passage in hACE2 mice (mixed them up with BALB/c mice). The major papers Miller relied on have been seriously challenged since the debate. See Stoyan and Chiu (2024), Weissman (2024), Bloom (2023) and Lv et al (2024). Overall the circumstantial evidence makes lab v plausible: Peter admitted getting this wrong during the debate. I think this very minor point about mice mutations was approximately his only mistake in 15 hours of debating, and he admitted it as soon as he noticed. Biorealism somehow heard about this (obviously not through watching the debate, as we’ll see in a moment), then left about 20-30 comments starting with it, under various accounts, on various platforms, as if it somehow discredited Peter. This is making me somewhat less charitable to him and his 16 arguments than I would be otherwise. 1. Chinese researchers Botao & Lei Xiao observed lab origin was likely given the nearest known relatives to SARS-CoV-2 were far from Wuhan. Wuhan Institute of Virology (WIV) sampled SARS-related bat coronaviruses where the nearest relatives are found in Yunnan, Laos and Vietnam ~1500km away. They refuse to share their records. The ancestral viruses of SARS were found equally far from where SARS spilled over into humans, so we know it’s possible (and likely) for viruses to travel that far. 2. Patrick Berche, DG at Institut Pasteur in Lille 2014-18, notes you would expect secondary outbreaks if it arose via the live animal trade. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234839/ There are constant outbreaks of weird coronaviruses in animal handlers. See eg this paper, which estimates about 60,000 of these per year. None of these ever go anywhere, because the farmers are in rural areas that aren’t dense enough to sustain a high R0, and the epidemic fizzles out after a single digit number of cases. Any early outbreaks of COVID would have vanished into this long and mostly unnoticed list. 3. Molecular data: Only sarbecovirus with a furin cleavage site. Well adapted to human ACE2 cells. Low genetic diversity indicating a lack of prior circulation (Berche 2023). Restriction site SARS-CoV-2 BsaI/BsmBI restriction map falls neatly within the ideal range for a reverse genetics system and used previously at WIV and UNC. Ngram analysis of the codon usage per Professor Louis Nemzer https://twitter.com/BiophysicsFL/status/1667232580255490053?t=IJgitS5cw364ioclzVWxaA&s=19 The SARS2 backbone is very low in CG and CpG. While the 12-nt insert that gives it the FCS is extremely high in both. Almost as if it was some kind of chimera of a consensus sequence and a codon-optimized polybasic cleavage site? https://twitter.com/BiophysicsFL/status/1752800486837678377?t=EpIRgyybJVaPgeMP5xdstA&s=19 https://www.biorxiv.org/content/10.1101/2022.10.18.512756v1 https://link.springer.com/article/10.1007/s10311-021-01211-0?fbclid=IwAR1HMUMtLIAFOFppVasQDeoIAYrVhP8j4YoPO4wnaTOUiKLsllZl_oKryOw Most of this was discussed extensively in the second session of the debate, which I recommend. The CGG-CGG arginine codon usage is particularly unusual but used in synthetic biology. I asked a synthetic biologist about this. He said: » “Nope. I would literally never do this if I was designing a small insert (maybe I wouldn't notice if it happened by chance with ~1 in 25 odds in a naive codon optimization algorithm as part of a larger sequence). High GC% is bad. Tandem repeat is worse. Several other perfectly fine arginine codons. And I wouldn't engineer a viral genome using human codon usage. An engineer would not do it.” 4. DEFUSE full proposal: virus 20% different from SARS1, consensus seq assembled with 6 segments, without disrupting coding seq, BsmBI order, FCS. SARS2: 20% different than SARS1, 6 evenly spaced fragments w BsmBI and BsaI restriction sites, FCS. Jesse Bloom, Jack Nunberg, Robert Townley, Alexandre Hassanin have observed this workflow could have lead to SARS-CoV-2. Work often begins before funding sought or goes ahead anyway. Re: 4 - Also scattered across second section of debate, also not going to retread 5. Market cases were all lineage B. Lv et al (2024) indicates there was a single point of emergence and A came before B. So market cases not the primary cases. See also Bloom (2021), Kumar et al (2022). Peter Ben Embarek said there were likely already thousands of cases in Wuhan in December 2019.https://t.co/50kFV9zSb6 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/34398234/ https://academic.oup.com/bioinformatics/article/38/10/2719/6553661 There was a Lineage A sample in the market, lab leak proponents just try to ignore/dismiss/conspiracize it away. The first two known Lineage A cases were very close to the market. Lv (is this even a real name? It sounds like Roman numeral? But I guess that’s what you expect in a country ruled by someone named Xi) found some weird COVID variants in Shanghai that might or might not mean anything; you can see some discussion of the implications here, but I don’t think they’re strong evidence either way. If A was first, it means some really weird stuff coincidences have to happen to give us the spread rates and genetic clock data we get, but they’re not necessarily weirder in the zoonosis hypothesis than the lab leak one. The claim that there were “thousands of cases in Wuhan in December 2019” is very easy to disprove by doubling rate arguments like the one above, by the blood bank study mentioned above, by the WHO’s failed case search, and by many other lines of argument. 6. Evidence for lineage A in the market is based on a low quality sample according to Liu et. al. (2023). I really think lab leakers need to decide whether they think China is a sinister actor trying to cover up the truth, or whether they should trust every offhand comment by Chinese government officials as gospel. Dr. Liu doesn’t explain in what sense he thinks the Lineage A sample is “low-quality”, and the Western scientists who I asked about this said they didn’t understand this complaint and that the sample was fine. A Western team re-analyzing the same sample describes it as “conclusively contain[ing] Lineage A.” I think most lab leakers have switched from trying to deny the genetics to claiming that this was “contamination”, which also doesn’t make sense (the sample is genetically very early). Note that aside from this sample, the first two Lineage A cases discovered were both very close to the wet market. 7. Bloom (2023) shows market samples do not support market origin. There is also no evidence of transmission in the claimed susceptible animals elsewhere. https://academic.oup.com/ve/advance-article/doi/10.1093/ve/vead089/7504441 Discussed extensively in my article as well as the first section of the debate. 8. Lineage A and B only two mutations apart. François Ballox, Bloom and Virginie Courtier-Orgogozo note this is unlikely to reflect two separate animal spillovers as opposed to incomplete case ascertainment of human to human transmission (Bloom 2021). Discussed extensively in my article as well as the first section of the debate. 9. Sampling bias. George Gao, Chinese CDC head at the time, acknowledged to the BBC stating they may have focused too much on and around the market and missed cases on the other side of the city. David Bahry outlines the documented bias. Michael Weissman has shown this mathematically. https://journals.asm.org/doi/10.1128/mbio.00313-23 https://academic.oup.com/jrsssa/advance-article-abstract/doi/10.1093/jrsssa/qnae021/7632556 Re: Dr. Gao, see above comment about Chinese officials. See the section Ascertainment Bias below for why I disagree with this specific claim, which also addresses the Michael Weissman argument. 10. Spatial statistics experts show the Worobey claim the market was the early epicentre was flawed. https://academic.oup.com/jrsssa/advance-article-abstract/doi/10.1093/jrsssa/qnad139/7557954 Re: 10 - See Confirmation Of The Centrality Of The Huanan Market Among Early COVID-19 Cases, a response to the paper you cite: The centrality of Wuhan's Huanan market in maps of December 2019 COVID-19 case residential locations, established by Worobey et al. (2022a), has recently been challenged by Stoyan and Chiu (2024, SC2024). SC2024 proposed a statistical test based on the premise that the measure of central tendency (hereafter, "centre") of a sample of case locations must coincide with the exact point from which local transmission began. Here we show that this premise is erroneous. SC2024 put forward two alternative centres (centroid and mode) to the centre-point which was used by Worobey et al. for some analyses, and proposed a bootstrapping method, based on their premise, to test whether a particular location is consistent with it being the point source of transmission. We show that SC2024's concerns about the use of centre-points are inconsequential, and that use of centroids for these data is inadvisable. The mode is an appropriate, even optimal, choice as centre; however, contrary to SC2024's results, we demonstrate that with proper implementation of their methods, the mode falls at the entrance of a parking lot at the market itself, and the 95% confidence region around the mode includes the market. Thus, the market cannot be rejected as central even by SC2024's overly stringent statistical test. I think this response is pretty strong. In one analysis, they show that even though the other paper’s methodology is worse than theirs, if you apply it correctly (instead of inappropriately excluding various cases like the paper’s authors did), the center of all early cases in Hubei province lands on the wet market parking lot. In another analysis, they show that the other paper’s recommended tests wouldn’t have correctly pointed to the offending water pump in the famous John Snow cholera outbreak, but theirs would have. Still, I think it’s useful to supplement fancy statistics with normal common sense, so I recommend just looking at the map of early cases: …and deciding whether you think the assumptions behind a specific statistical test are likely to debunk the idea that cases are centered around the wet market. 11. Wuhan used as a control for a 2015 serological study on SARS-related bat coronaviruses due to its urban location. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6178078/ I don’t know why this point is supposed to matter. If you mean that Wuhan isn’t directly exposed to bats, nobody ever said it was. The zoonotic theory is that wildlife carted in from other areas of China started the pandemic in the wet market. 12. Superspreader events also seen at wet markets in Beijing and Singapore (Xinfadi and Jurong). This was discussed very extensively in the debates, both in section 1 and section 3. Wet markets weren’t “superspreader locations” - in fact, the disease spread no more quickly there than anywhere else. They were the first place in those cities that the pandemic started, due to contaminated animal products. If anything, this supports zoonosis. See also my discussion with Saar on this point below. 13. WIV refuse to share their records with NIH who terminated subaward in 2022. Wider suspension over biosafety concerns. https://www.bloomberg.com/news/articles/2023-07-18/us-suspends-wuhan-institute-funds-over-covid-stonewalling Although WIV has not been especially forthcoming, some of their databases were leaked in various ways and showed that they did not have any viruses capable of transforming into COVID. 14. PLA involvement at WIV and MERS research prior to SARS-COV-2. MERS features several similarities with SARS-CoV-2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7022351/ I can’t even tell what conspiracy theory you’re trying to propose with this one; if you spell it out I can try to explain why it might be false. 15. SARS1 leaked several times and SARS-COV-2 has leaked from a BSL-3 lab in Taiwan. Agreed that SARS leaked several times. It also spilled over from animals several times. During the debate, a lab leak rate of once per lab per 500 years was proposed (everyone agreed to steelman this by 10x for WIV numbers); I would be interested to know whether anything about the study of SARS challenges that number. 16. Unpublished infectious clone identified from Wuhan contradicting arguments such reverse genetics systems would be published. https://www.biorxiv.org/content/10.1101/2023.02.12.528210v1.full I asked some scientists about this paper and here’s what they told me. Wuhan University sequenced some rice. In the middle of the sequence, there’s an unexpected sequence from a common coronavirus, HKU4. The most likely explanation is that someone else in Wuhan was working on the coronavirus and there was cross-contamination. Plausibly this is Wuhan Institute of Virology, who is known to work with coronaviruses. This is cool detective work, but it’s not clear what it’s supposed to prove. I think some lab leakers are using it to prove that WIV can do reverse genetics, but they admitted this already in a published paper so that’s not too helpful. I think others are using it to prove WIV had “secret viruses” in their catalogue, but the rice virus wasn’t secret, it was HKU4, which is common and which WIV has already published papers about. 1.6: DrJayChou’s 7 Arguments Once again, I cannot stress enough how much better a take you might have on this debate if you watch it. “The first known case predates the market outbreak by a month” - this is not the consensus position. I cannot say for sure what Dr. Chou means by this, but I suspect he’s referring to one of the many claims to this effect that Peter effectively debunked during the debate (Connor Reed, Mr. Chen, the 92 cases, Brazil, etc).
Xinhua

Xinhua is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 07, 2023 and June 07, 2023. The archive places it in contexts such as "He probably has some good antibodies to whatever Xinhua is peddling". It most often appears alongside 747, America, America Against America.

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Xinhua
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1
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June 07, 2023
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June 07, 2023
June 07, 2023 · Original source
Wang Huning grew up in one of the world’s tightest authoritarian societies, where all the news is a carefully-managed propaganda campaign to make the government look great. He probably has some good antibodies to whatever Xinhua is peddling, but, I’m afraid, might not have been prepared for America’s particular pathologies. So when people told him Americans were quitting work to suck up fat welfare checks, he believed them. When people told him that there were a million teenage runaways in America, he believed them. And when people told him that motorcycle gangs with Treasurers and War Lords were crucifying women with impunity, he believed that too. Probably all of these things are sort of happening, somewhere. But probably Wang ended up thinking they were happening much more often than they were.
XKCD What If

XKCD What If is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between December 17, 2024 and December 17, 2024. The archive places it in contexts such as "One possible answer in the second half of this XKCD What If". It most often appears alongside 2016 US Presidential election, ACX Grant, AI.

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XKCD What If
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1
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December 17, 2024
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December 17, 2024
December 17, 2024 · Original source
33: Seen on X: “Gas mileage in gallons per mile has units of area. What area does this correspond to?” (h/t @eigenrobot). One possible answer in the second half of this XKCD What If.